In communication networks, particularly wireless networks, information is typically exchanged in transport blocks error-protected by a convolutional code, i.e., as code blocks. A receiver locates the code block in a received signal and Viterbi decoding is performed to retrieve the transport block.
Mobile communication standards, including the Long-Term Evolution (LTE, also known as Evolved Universal Terrestrial Radio Access, E-UTRA) and Universal Mobile Telecommunications System (UMTS) standards of 3GPP, convey control information to a User Equipment (UE) in transport blocks, which further comprise a Cyclic Redundancy Check (CRC) value of the control information for error detection. The UE has to completely decode the received signal before validating the control information in the transport block based on the CRC value. In case of a negative CRC, the control information will be discarded, i.e. computation time and power for the decoding has been wasted. This waste is particularly unfavourable for a battery-operated mobile receiver with limited computational and power resources.
The resource demands for decoding are particularly high for modern tail-biting convolutional codes having significantly increased decoding complexity. Moreover, for cellular networks addressing the UE by an identifier included in the transport block, the UE has to decode a large number of code blocks in order to identify the transport block actually addressed to the UE.
As stated above, a decision whether to process or discard the control information is conventionally based on the CRC value. Because of the finite number of bits reserved for the CRC value, there is a small but non-negligible probability of erroneously identifying control information as addressed to the UE or even noise signals as valid information, typically in the order of 10−4. Since content of the incorrect control information is close to random, processing the incorrect control information can lead to undefined receiver states and can cause further traffic of retransmission requests. For example, network throughput of useful data can be reduced, radio and computational resources may be wasted, a processing stage may enter an undefined state, and a communication partner may have to process positive or negative acknowledgements for transport blocks that were never sent.